1. Field of the Invention
The present invention relates to a technique of measuring the position and orientation of an image sensing device.
2. Description of the Related Art
In a mixed reality system which presents an image formed by synthesizing, for example, a physical space with a virtual space to a user, it is necessary to measure the position and orientation of an image sensing device for sensing the physical space.
As a method of measuring the position and orientation of an image sensing device, conventionally, a method using an index whose three-dimensional position is known has been disclosed. In this method, the position and orientation of an image sensing device are estimated by optimizing an objective function which uses the distance between a projection position where the three-dimensional position of an index is projected onto a sensed image using the coarse position and orientation of the image sensing device and the position of the index detected on the sensed image.
Additionally, a method using, as a known index, the boundary between object planes included in a physical space has been disclosed. The boundary between observable object planes will be referred to as an “edge” hereinafter.
Non-patent reference 1 discloses the following method. A measurement line segment of a measurement target object is projected onto a sensed image using the coarse position and orientation of an image sensing device. The position and orientation are estimated using, as an objective function, the distance between the projected line segment and an edge detected from the sensed image in correspondence with the measurement line segment.
An outline of this method will be described below.
Using an estimated coarse position and orientation of an image sensing device, a measurement line segment of a measurement target object is projected onto an image sensed by the image sensing device.
Pixels around the measurement line segment projected onto the sensed image are searched to calculate a position of an area (edge area) where the density locally changes.
Optimization calculation is performed such that the distance between the position of the edge area and the projected measurement line segment becomes small.
The estimated coarse position and orientation of the image sensing device are updated in accordance with the optimization calculation.
The position and orientation estimation using a measurement line segment of a measurement target object can be executed when the shape of the measurement target object is known, and the three-dimensional model of the measurement target object can be obtained. Hence, the application range of this method is wide.
Additionally, edge search on the sensed image is done for only the peripheral image of the projected measurement line segment. This shortens the process time as compared to a method of obtaining the distance to a model after an edge is detected from a whole sensed image by image processing. For this reason, this position and orientation estimation method is used for registration of an image sensing device which requires real-time processing for, for example, a mixed reality.
In non-patent reference 1, a measurement target object having a relatively simple shape and coarse measurement line segments whose search areas do not overlap are used.
Since an actual environment includes illumination and objects other than the measurement target object, many edges other than those of the measurement target object are also observed.
If the correspondence between measurement line segments and edges is insufficient, the difference between a measurement line segment and the edge of another measurement line segment may be calculated, and the solution may converge to an erroneous value. Non-patent reference 2 discloses a method of minimizing an objective function while holding a plurality of correspondences on the assumption that a plurality of edges are observed.
One of a plurality of observed edges is associated with a measurement line segment projected onto a sensed image, and optimization calculation is performed such that the distance between them becomes small. Assumption about the association is repeatedly made several times, and the solution is allowed to converge by minimizing the error. This allows robust position and orientation estimation even in an environment including edges other than those of the measurement target.
[Non-Patent Reference 1] Tom Drummond and Roberto Cipolla, “Real-time visual tracking of complex structures”, IEEE Transaction of Pattern Analysis and Machine Intelligence, Vol. 24, No. 7, pp. 932-946, 2002
[Non-Patent Reference 2] L. Vacchetti, V. Lapetit, and P. Fua, “Combining edge and texture information for real-time accurate 3D camera tracking”, Proceedings of International Symposium on Mixed and Augmented Reality, pp. 48-57, 2004
If an arbitrary measurement target object is used, measurement line segments may have a high density. In a measurement target object such as a jungle gym formed from a wire-frame, the search areas of the respective measurement line segments projected onto a sensed image overlap each other. In this case, an edge search process in the overlapping search areas is useless.
The relationship between the measurement line segments is not taken into consideration. For this reason, near a corner of the measurement target object or for parallel measurement line segments in close vicinity on the sensed image, it may be impossible to correctly recognize the correspondence between a measurement line segment and an edge.
When a measurement target object is located far away, its size on a sensed image is small. Consequently, the interval between measurement line segments is small, and the search areas overlap with a high probability. The correspondence relationship between a detected edge and a measurement line segment is often erroneously recognized, affecting the position and orientation estimation result.